(
self,
kernel_size: int = 3,
spatial_axes: Sequence[int] | int | None = None,
normalize_kernels: bool = True,
normalize_gradients: bool = False,
padding_mode: str = "reflect",
dtype: torch.dtype = torch.float32,
)
| 1058 | backend = [TransformBackends.TORCH] |
| 1059 | |
| 1060 | def __init__( |
| 1061 | self, |
| 1062 | kernel_size: int = 3, |
| 1063 | spatial_axes: Sequence[int] | int | None = None, |
| 1064 | normalize_kernels: bool = True, |
| 1065 | normalize_gradients: bool = False, |
| 1066 | padding_mode: str = "reflect", |
| 1067 | dtype: torch.dtype = torch.float32, |
| 1068 | ) -> None: |
| 1069 | super().__init__() |
| 1070 | self.padding = padding_mode |
| 1071 | self.spatial_axes = spatial_axes |
| 1072 | self.normalize_kernels = normalize_kernels |
| 1073 | self.normalize_gradients = normalize_gradients |
| 1074 | self.kernel_diff, self.kernel_smooth = self._get_kernel(kernel_size, dtype) |
| 1075 | |
| 1076 | def _get_kernel(self, size, dtype) -> tuple[torch.Tensor, torch.Tensor]: |
| 1077 | if size < 3: |
nothing calls this directly
no test coverage detected